Policy and Economic Considerations for Frailty Screening in the Canadian Healthcare System
Bibliographic record
Abstract
Canada faces significant policy and economic challenges related to healthcare for frail older adults. Annual per capita healthcare costs for people over age 65 are five times those for people under 65. Flat economic growth and an aging workforce decrease tax revenue, which funds 70% of health spending. Governments are shifting policy to enhance person-centered care and shifting spending from hospitals to primary and community care. Recognizing that frailty and evidence-based frailty screening can contribute directly to reform initiatives, what are the policy and economic considerations, both nationally and internationally, around frailty screening that will benefit patients, families and/or the wider health system? Based on key informant interviews, we present recommendations for approaching policy and economic challenges in frailty through the following healthcare policy instruments: financing, funding, legislation, regulation, technology, interdisciplinary care, person-centered service and health promotion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".